Field
The present invention relates to systems and methods for providing cost-efficient charge planning for electric or plug-in hybrid vehicles based on a predicted combination of routes of the vehicle and costs of energy at various destinations of the vehicle.
Description of the Related Art
The number of electric and plug-in hybrid vehicles that are in use is increasing for many reasons including the rising cost and potentially harmful environmental effects of gasoline. These vehicles can typically be charged (i.e., receive electrical energy via an external charger coupled to a power source) and store the received electrical energy into an onboard battery. The quantity and availability of these chargers has been steadily increasing due to the rising popularity of these vehicles. For example, electrical and plug-in hybrid vehicle owners now can install external chargers for powering these vehicles in their homes and many office buildings now have external chargers in their parking lots for employees working in the buildings.
The cost of electrical energy can vary greatly based on a time of day and the particular power source from where the energy is received. For example, energy is typically more expensive during the daytime than at nighttime, and may be more expensive at an office building than at the user's house. Some users will charge their vehicle at any location at which a power source is available, regardless of the cost, in order to reduce the likelihood of total depletion of available electrical energy during a trip. Even if these users desire to reduce charging costs, they may not take any action due to the difficulty in learning and remembering the cost of power at various locations and times.
Thus, there is a need in the art for methods and systems that can determine a cost-efficient charging plan for an electric vehicle or a plug-in hybrid vehicle based on costs of energy at various locations and times of day.